Tuberculosis (TB) is a widespread disease that crosses the human and animal health boundaries, with infection being reported in wildlife, from temperate and subtropical to arctic regions. Often, TB in wild species is closely associated with disease occurrence in livestock but the TB burden in wildlife remains poorly quantified on a global level. Through meta-regression and systematic review, this study aimed to summarize global information on TB prevalence in commonly infected wildlife species and to draw a global picture of the scientific knowledge accumulated in wildlife TB. For these purposes, a literature search was conducted through the Web of Science and Google Scholar. The 223 articles retrieved, concerning a 39-year period, were submitted to bibliometric analysis and 54 publications regarding three wildlife hosts fulfilled the criteria for meta-regression. Using a random-effects model, the worldwide pooled TB prevalence in wild boar is higher than for any other species and estimated as 21.98%, peaking in Spain (31.68%), Italy (23.84%) and Hungary (18.12%). The pooled prevalence of TB in red deer is estimated at 13.71%, with Austria (31.58%), Portugal (27.75%), New Zealand (19.26%) and Spain (12.08%) positioning on the top, while for European badger it was computed 11.75%, peaking in the UK (16.43%) and Ireland (22.87%). Despite these hard numbers, a declining trend in wildlife TB prevalence is apparent over the last decades. The overall heterogeneity calculated by multivariable regression ranged from 28.61% (wild boar) to 60.92% (red deer), indicating that other unexplored moderators could explain disease burden. The systematic review shows that the most prolific countries contributing to knowledge related with wildlife TB are settled in Europe and Mycobacterium bovis is the most reported pathogen (89.5%). This study provides insight into the global epidemiology of wildlife TB, ascertaining research gaps that need to be explored and informing how should surveillance be refined.
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http://dx.doi.org/10.1111/tbed.13948 | DOI Listing |
Ann Intern Med
January 2025
Durham VA Health Care System, Durham; and Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina (K.M.G.).
Background: Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations.
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Data Sources: MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024.
J Med Internet Res
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Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
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View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Basic and Community Nursing, School of Nursing, Nanjing Medical University, NanJing, China.
Background: Telehealth interventions can effectively support caregivers of people with dementia by providing care and improving their health outcomes. However, to successfully translate research into clinical practice, the content and details of the interventions must be sufficiently reported in published papers.
Objective: This study aims to evaluate the completeness of a telehealth intervention reporting in randomized controlled trials (RCTs) conducted for caregivers of people with dementia.
JMIR Ment Health
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Division of Psychology and Mental Health, University of Manchester, Manchester, United Kingdom.
Background: Digital mental health interventions (DMHIs) to monitor and improve the health of people with psychosis or bipolar disorder show promise; however, user engagement is variable, and integrated clinical use is low.
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Methods: A systematic search of 7 databases identified empirical studies reporting qualitative or quantitative data about factors affecting staff or patient engagement with DMHIs aiming to monitor or improve the mental or physical health of people with psychosis or bipolar disorder.
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